1D 1H Nuclear Magnetic Resonance Research Articles

Physiochemical Characterization and Stability of Lipidic Cubic Phases by Solution NMR.

Lipidic inverse bicontinuous cubic phases (LCPs), formed via the spontaneous self-assembly of lipids such as monoolein, have found increasing applications in the stabilization and crystallization of integral membrane proteins for structural characterization using X-ray crystallography. Their use as effective drug release matrices has also been demonstrated. Nuclear magnetic resonance (NMR) spectroscopy, both solution and solid state, has previously been employed for the characterization of LCPs and related systems. Herein, we report a number of novel features of solution NMR for probing the fundamental composition and structural properties of monoolein-based LCPs. These include (1) more complete assignments of both 1H and 13C chemical shifts, (2) direct quantification of hydration level in LCPs using one-dimensional (1D) 1H NMR, and (3) monitoring longer-term stability of LCPs and evaluating alterations introduced into standard LCPs at the submolecular level.

Nuclear magnetic resonance-based targeted profiling of urinary acetate and citrate following cyclophosphamide therapy in patients with lupus nephritis.

Metabolomics, the study of global alterations in small metabolites, is a useful tool to look for novel biomarkers. Recently, we reported a reprogramming of the serum metabolomic profile by nuclear magnetic resonance (NMR) spectroscopy following treatment in lupus nephritis (LN). This study aimed to compare the urine excretory levels of citrate and acetate in patients with biopsy-proven LN before and six months after cyclophosphamide induction therapy and to evaluate their correlation with the Systemic Lupus Erythematosus Disease Activity Index 2K (SLEDAI 2K) and renal SLEDAI. Urine obtained from LN patients (N = 18, 16 female) at diagnosis and six months following induction therapy with cyclophosphamide and healthy controls (HC; N = 18, median age = 35 years, all female) were stored at -80°C. Metabolomic profiling was done using high resolution 800 MHz 1D 1H NMR spectroscopy. The urinary ratio of metabolites was calculated as (metabolite×1000)/creatinine. Disease activity was measured using the SLEDAI. Metabolomic profiles were compared between groups and correlated with clinical parameters. Compared to HC, LN patients had significantly lower median urinary citrate/creatinine levels (LN = 18.26, range 12.80-27.62; HC = 107.7, range 65.39-138.4; p < 0.0001) which significantly increased after six months of cyclophosphamide treatment (51.05, range 11.51-170.2; p = 0.03). LN patients also differed from HC by having a higher mean urinary acetate/creatinine ratio (LN = 17.44, range 11.6-32.7; HC = 9.61, range 7.97-13.71; p = 0.054) with a non-significant fall in values after six months of treatment. The Area under curve for differentiating LN from HC for urinary citrate was 0.9136, and urinary acetate was 0.6883. The urinary acetate levels correlated with SLEDAI (r = 0.337, p = 0.048). Urinary citrate levels correlated positively with C3 (r = 0.362, p = 0.03) and negatively with urine protein/creatinine (r = -0.346, p = 0.039). Urinary citrate, which reflects dampened aerobic glycolysis and oxidative phosphorylation, improved significantly and is a potential non-invasive biomarker for diagnosis and monitoring treatment response in LN.

Abstract P4-10-25: Pretreatment serum metabolome predicts PFS in first-line trastuzumab-treated metastatic breast cancer

Abstract Background: Cancer cells have altered metabolism, which contributes to their ability to proliferate, survive in unusual microenvironments, and invade other tissues. Measuring the complete set of metabolites in an individual (i.e. the metabolome) provides a functional readout for cellular pathways. Further, changes in the metabolome can be correlated with disease status, prognosis and progression. Using a metabolomics platform and machine learning algorithms, biomarker signatures can be identified to predict response to therapy. Metabolite analysis of pretreatment plasma has shown promise for predicting response in a small retrospective study of the CDK 4/6 inhibitors palbociclib and ribociclib in hormone receptor-positive metastatic breast cancer (Zhang B et al, ASCO 2019 Abstr 3043). HER2-positive metastatic breast cancer patients have significant heterogeneity in response and progression-free survival (PFS) to HER2-targeted therapy. Here we retrospectively evaluated the pretreatment serum metabolome for association with PFS in a cohort of trastuzumab-treated metastatic breast cancer patients from a single institution. Methods: Pretreatment serum from 26 HER2-positive trastuzumab-naive metastatic breast cancer patients who were treated with first-line trastuzumab and chemotherapy were included in this exploratory analysis. Metabolites were extracted from previously frozen serum (1 mL) using ice-cold methanol and chloroform. The resulting metabolites were isolated and quantified using an unbiased, non-destructive, nuclear magnetic resonance (NMR)-based profiling platform (Olaris, Inc., Cambridge, MA). The serum was analyzed via 1D 1H NMR and 2D 13C-1H heteronuclear single quantum coherence spectroscopy (HSQC) using customized non-uniform sampling (NUS) techniques and processed with proprietary Olaris software. Supervised and unsupervised machine learning algorithms were used to identify patients with shorter and longer PFS to trastuzumab-based therapy. Results: The median PFS for this cohort was 301 days. Patients were subdivided into early progressors (PFS &amp;lt; 301 days) and late progressors (PFS ≥ 301 days). 23 metabolite resonance levels were statistically different between the two groups (KW test p&amp;lt;0.05, 11 metabolites expected by chance). Using advanced machine learning we constructed a model based on 5 metabolite resonances that showed significant discriminatory ability with an AUC of 0.964 using receiver-operating curve (ROC) analysis. 21 of the 26 patients received trastuzumab and chemotherapy as a first-line therapy, while the remaining 5 patients received first-line trastuzumab with subsequent chemotherapy, after 1 or more lines of previous chemotherapy for metastatic disease. We repeated our analysis using only the first-line therapy subgroup and identified a partially overlapping set of metabolite resonances that could nearly perfectly discriminate early and late progressors with an AUC of 0.973. Further efforts are underway to confirm the identity of these metabolites. Conclusions: Metabolic profiling of pretreatment serum using NMR was successful in identifying a biomarker signature that predicted PFS to trastuzumab in HER2-positive metastatic breast cancer. Expanded metabolome analysis is warranted in larger cohorts and clinical trials to confirm that this serum biomarker signature predicts PFS to trastuzumab therapy, particularly in the first-line setting. Further, by identifying the metabolites and metabolic pathways that differ between early and late progressors, it may be possible to identify novel targets and/or suggest combination treatments in the HER2-positive metastatic breast cancer setting. Citation Format: Elizabeth O'Day, Kim Leitzel, Suhail M Ali, Bo Zhang, Chen Dong, Haiwei Gu, Xiajian Shi, Joseph J Drabick, Leah Cream, Monali Vasekar, Hyma V Polimera, Vinod Nagabhairu, Prashanth Moku, Ashok Maddukuri, Harry Menon, Neha Pancholy, Walter P Carney, Wolfgang Koestler, Allan Lipton. Pretreatment serum metabolome predicts PFS in first-line trastuzumab-treated metastatic breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-10-25.

The mechanism of pulsed electric field (PEF) targeting location on the spatial conformation of pine nut peptide

In this study, the pine nut peptides, Lys-Asp-His-Cyc-His (KDHCH), was used as the molecule dynamics (MD) simulations subject, which has been proved that the antioxidant activity was improved after pulse electric field (PEF) treatment and the secondary structure was changed as the circular dichroism (CD) results showed. In the present study, we applied the MD simulation to discover the mechanism of the antioxidant activity improvement. The MD results showed that with the PEF treatment of 15 kV/cm, the oxygen atoms of KDHCH changed a lot, especially the atoms No.32 and No.63, of which the distance difference value was −3.02 nm, compared with the 0 kV/cm PEF treatment. The result showed an approach trend between residues Lys-and His-and the α-C atom of Lys, Cys-and His-all got closer after the PEF treatment, which means the structure became tight after the PEF treatment. However, the results of 45 kV/cm PEF treatment presented more effects on the change of KDHCH. The calculations of oxygen atoms show an approach trend between residues Lys, Asp-and His. The α-C atom of Lys, Cys-and His-all got closer after the PEF treatment, which means the structure became tight after the PEF treatment and proved the results of the calculations of the oxygen atoms. The structures of PEF treated and untreated peptide samples were measured by 1D and 2D nuclear magnetic resonance (NMR) in order to verify the results of the molecular dynamics simulations. The 8.37–8.40 ppm (—NH- in chain) and 8.84–8.88 ppm (—NH- in chain) appeared left shift, while at the 8.45–8.47 ppm (-NH- in chain) occurred a right shift. The 7.82 ppm (—NH- in imidazole ring) on His-shifted left after PEF treatment, which reached 7.84 ppm by the 1D-1H NMR spectroscopy. Moreover, the long-range connectivity between —NHα (8.78 ppm) on 2H-ASP and —CHα (2.72 ppm) on 1H-LYS; —SH (2.50 ppm) on 4H-CYS and —OH (3.53 ppm) on 5H-HIS all appeared in spectra of the PEF treatment sample. This study will also be helpful to further mechanism exploration.

Metabolomic Analysis of Platelets of Patients With Aspirin Non-Response.

Background: Aspirin is the most commonly used antiplatelet agent for the prevention of cardiovascular diseases. However, a certain proportion of patients do not respond to aspirin therapy. The mechanisms of aspirin non-response remain unknown. The unique metabolomes in platelets of patients with coronary artery disease (CAD) with aspirin non-response may be one of the causes of aspirin resistance.Materials and Methods: We enrolled 29 patients with CAD who were aspirin non-responders, defined as a study subject who were taking aspirin with a platelet aggregation time less than 193 s by PFA-100, and 31 age- and sex-matched patients with CAD who were responders. All subjects had been taking 100 mg of aspirin per day for more than 1 month. Hydrophilic metabolites from the platelet samples were extracted and analyzed by nuclear magnetic resonance (NMR). Both 1D 1H and 2D J-resolved NMR spectra were obtained followed by spectral processing and multivariate statistical analysis, such as partial least squares discriminant analysis (PLS-DA).Results: Eleven metabolites were identified. The PLS-DA model could not distinguish aspirin non-responders from responders. Those with low serum glycine level had significantly shorter platelet aggregation time (mean, 175.0 s) compared with those with high serum glycine level (259.5 s). However, this association became non-significant after correction for multiple tests.Conclusions: The hydrophilic metabolic profile of platelets was not different between aspirin non-responders and responders. An association between lower glycine levels and higher platelet activity in patients younger than 65 years suggests an important role of glycine in the pathophysiology of aspirin non-response.

ASICS: an R package for a whole analysis workflow of 1D 1H NMR spectra.

In metabolomics, the detection of new biomarkers from Nuclear Magnetic Resonance (NMR) spectra is a promising approach. However, this analysis remains difficult due to the lack of a whole workflow that handles spectra pre-processing, automatic identification and quantification of metabolites and statistical analyses, in a reproducible way. We present ASICS, an R package that contains a complete workflow to analyse spectra from NMR experiments. It contains an automatic approach to identify and quantify metabolites in a complex mixture spectrum and uses the results of the quantification in untargeted and targeted statistical analyses. ASICS was shown to improve the precision of quantification in comparison to existing methods on two independent datasets. In addition, ASICS successfully recovered most metabolites that were found important to explain a two level condition describing the samples by a manual and expert analysis based on bucketing. It also found new relevant metabolites involved in metabolic pathways related to risk factors associated with the condition. ASICS is distributed as an R package, available on Bioconductor. Supplementary data are available at Bioinformatics online.

1D "Spikelet" Projections from Heteronuclear 2D NMR Data-Permitting 1D Chemometrics While Preserving 2D Dispersion.

Nuclear magnetic resonance (NMR) spectroscopy is a powerful tool for the non-targeted metabolomics of intact biofluids and even living organisms. However, spectral overlap can limit the information that can be obtained from 1D 1H NMR. For example, magnetic susceptibility broadening in living organisms prevents any metabolic information being extracted from solution-state 1D 1H NMR. Conversely, the additional spectral dispersion afforded by 2D 1H-13C NMR allows a wide range of metabolites to be assigned in-vivo in 13C enriched organisms, as well as a greater depth of information for biofluids in general. As such, 2D 1H-13C NMR is becoming more and more popular for routine metabolic screening of very complex samples. Despite this, there are only a very limited number of statistical software packages that can handle 2D NMR datasets for chemometric analysis. In comparison, a wide range of commercial and free tools are available for analysis of 1D NMR datasets. Overtime, it is likely more software solutions will evolve that can handle 2D NMR directly. In the meantime, this application note offers a simple alternative solution that converts 2D 1H-13C Heteronuclear Single Quantum Correlation (HSQC) data into a 1D “spikelet” format that preserves not only the 2D spectral information, but also the 2D dispersion. The approach allows 2D NMR data to be converted into a standard 1D Bruker format that can be read by software packages that can only handle 1D NMR data. This application note uses data from Daphnia magna (water fleas) in-vivo to demonstrate how to generate and interpret the converted 1D spikelet data from 2D datasets, including the code to perform the conversion on Bruker spectrometers.

Synovial Fluid Metabolites Differentiate between Septic and Nonseptic Joint Pathologies.

Osteoarthritis (OA), osteochondrosis (OC), and synovial sepsis in horses cause loss of function and pain. Reliable biomarkers are required to achieve accurate and rapid diagnosis, with synovial fluid (SF) holding a unique source of biochemical information. Nuclear magnetic resonance (NMR) spectroscopy allows global metabolite analysis of a small volume of SF, with minimal sample preprocessing using a noninvasive and nondestructive method. Equine SF metabolic profiles from both nonseptic joints (OA and OC) and septic joints were analyzed using 1D 1H NMR spectroscopy. Univariate and multivariate statistical analyses were used to identify differential metabolite abundance between groups. Metabolites were annotated via 1H NMR using 1D NMR identification software Chenomx, with identities confirmed using 1D 1H and 2D 1H 13C NMR. Multivariate analysis identified separation between septic and nonseptic groups. Acetate, alanine, citrate, creatine phosphate, creatinine, glucose, glutamate, glutamine, glycine, phenylalanine, pyruvate, and valine were higher in the nonseptic group, while glycylproline was higher in sepsis. Multivariate separation was primarily driven by glucose; however, partial-least-squares discriminant analysis plots with glucose excluded demonstrated the remaining metabolites were still able to discriminate the groups. This study demonstrates that a panel of synovial metabolites can distinguish between septic and nonseptic equine SF, with glucose the principal discriminator.

Spin System Modeling of Nuclear Magnetic Resonance Spectra for Applications in Metabolomics and Small Molecule Screening.

The exceptionally rich information content of nuclear magnetic resonance (NMR) spectra is routinely used to identify and characterize molecules and molecular interactions in a wide range of applications, including clinical biomarker discovery, drug discovery, environmental chemistry, and metabolomics. The set of peak positions and intensities from a reference NMR spectrum generally serves as the identifying signature for a compound. Reference spectra normally are collected under specific conditions of pH, temperature, and magnetic field strength, because changes in conditions can distort the identifying signatures of compounds. A spin system matrix that parametrizes chemical shifts and coupling constants among spins provides a much richer feature set for a compound than a spectral signature based on peak positions and intensities. Spin system matrices expand the applicability of NMR spectral libraries beyond the specific conditions under which data were collected. In addition to being able to simulate spectra at any field strength, spin parameters can be adjusted to systematically explore alterations in chemical shift patterns due to variations in other experimental conditions, such as compound concentration, pH, or temperature. We present methodology and software for efficient interactive optimization of spin parameters against experimental 1D-1H NMR spectra of small molecules. We have used the software to generate spin system matrices for a set of key mammalian metabolites and are also using the software to parametrize spectra of small molecules used in NMR-based ligand screening. The software, along with optimized spin system matrix data for a growing number of compounds, is available from http://gissmo.nmrfam.wisc.edu/ .

Automated metabolite identification from biological fluid 1H NMR spectra

Metabolite identification in biological samples using Nuclear Magnetic Resonance (NMR) spectra is a challenging task due to the complexity of the biological matrices. This paper introduces a new, automated computational scheme for the identification of metabolites in 1D 1H NMR spectra based on the Human Metabolome Database. The methodological scheme comprises of the sequential application of preprocessing, data reduction, metabolite screening and combination selection. The proposed scheme has been tested on the 1D 1H NMR spectra of: (a) an amino acid mixture, (b) a serum sample spiked with the amino acid mixture, (c) 20 blood serum, (d) 20 human amniotic fluid samples, (e) 160 serum samples from publicly available database. The methodological scheme was compared against widely used software tools, exhibiting good performance in terms of correct assignment of the metabolites. This new robust scheme accomplishes to automatically identify peak resonances in 1H-NMR spectra with high accuracy and less human intervention with a wide range of applications in metabolic profiling.

J-Resolved 1H NMR 1D-Projections for Large-Scale Metabolic Phenotyping Studies: Application to Blood Plasma Analysis.

1H nuclear magnetic resonance (NMR) spectroscopy-based metabolic phenotyping is now widely used for large-scale epidemiological applications. To minimize signal overlap present in 1D 1H NMR spectra, we have investigated the use of 2D J-resolved (JRES) 1H NMR spectroscopy for large-scale phenotyping studies. In particular, we have evaluated the use of the 1D projections of the 2D JRES spectra (pJRES), which provide single peaks for each of the J-coupled multiplets, using 705 human plasma samples from the FGENTCARD cohort. On the basis of the assessment of several objective analytical criteria (spectral dispersion, attenuation of macromolecular signals, cross-spectral correlation with GC-MS metabolites, analytical reproducibility and biomarker discovery potential), we concluded that the pJRES approach exhibits suitable properties for implementation in large-scale molecular epidemiology workflows.

NMR Profiling of Metabolites in Larval and Juvenile Blue Mussels (Mytilus edulis) under Ambient and Low Salinity Conditions

Blue mussels (Mytilus edulis) are ecologically and economically important marine invertebrates whose populations are at risk from climate change-associated variation in their environment, such as decreased coastal salinity. Blue mussels are osmoconfomers and use components of the metabolome (free amino acids) to help maintain osmotic balance and cellular function during low salinity exposure. However, little is known about the capacity of blue mussels during the planktonic larval stages to regulate metabolites during osmotic stress. Metabolite studies in species such as blue mussels can help improve our understanding of the species’ physiology, as well as their capacity to respond to environmental stress. We used 1D 1H nuclear magnetic resonance (NMR) and 2D total correlation spectroscopy (TOCSY) experiments to describe baseline metabolite pools in larval (veliger and pediveliger stages) and juvenile blue mussels (gill, mantle, and adductor tissues) under ambient conditions and to quantify changes in the abundance of common osmolytes in these stages during low salinity exposure. We found evidence for stage- and tissue-specific differences in the baseline metabolic profiles of blue mussels, which reflect variation in the function and morphology of each larval stage or tissue type of juveniles. These differences impacted the utilization of osmolytes during low salinity exposure, likely stemming from innate physiological variation. This study highlights the importance of foundational metabolomic studies that include multiple tissue types and developmental stages to adequately evaluate organismal responses to stress and better place these findings in a broader physiological context.

Advanced solvent signal suppression for the acquisition of 1D and 2D NMR spectra of Scotch Whisky.

A simple and robust solvent suppression technique that enables acquisition of high‐quality 1D 1H nuclear magnetic resonance (NMR) spectra of alcoholic beverages on cryoprobe instruments was developed and applied to acquire NMR spectra of Scotch Whisky. The method uses 3 channels to suppress signals of water and ethanol, including those of 13C satellites of ethanol. It is executed in automation allowing high throughput investigations of alcoholic beverages. On the basis of the well‐established 1D nuclear Overhauser spectroscopy (NOESY) solvent suppression technique, this method suppresses the solvent at the beginning of the pulse sequence, producing pure phase signals minimally affected by the relaxation. The developed solvent suppression procedure was integrated into several homocorrelated and heterocorrelated 2D NMR experiments, including 2D correlation spectroscopy (COSY), 2D total correlation spectroscopy (TOCSY), 2D band‐selective TOCSY, 2D J‐resolved spectroscopy, 2D 1H, 13C heteronuclear single‐quantum correlation spectroscopy (HSQC), 2D 1H, 13C HSQC‐TOCSY, and 2D 1H, 13C heteronuclear multiple‐bond correlation spectroscopy (HMBC). A 1D chemical‐shift‐selective TOCSY experiments was also modified. The wealth of information obtained by these experiments will assist in NMR structure elucidation of Scotch Whisky congeners and generally the composition of alcoholic beverages at the molecular level.

Metabolic Immunomodulation of Macrophage Polarization by Pseudomonas aeruginosa Biofilms

Despite extensive investment in better healthcare practices, hospital acquired infections (HAIs) remain a major public health concern. In 2011, the CDC's HAI Prevalence Survey identified 722,000 patients with infections contracted during treatment at acute care hospitals, resulting in 75,000 deaths. It has been well demonstrated that the establishment of bacterial biofilm in the wound is a major contributor to the failure of acute wound treatment and development of chronic, non‐healing wounds; however how the metabolic phenotype of a colonizing biofilm influences the wound healing process remains unknown. This gap in knowledge inhibits the development of effective treatment protocols and results in chronic wounds being the leading cause of non‐traumatic limb amputations. Herein, we define how metabolic exchange and metabolite competition between P. aeruginosa biofilms and macrophages promotes a pro‐inflammatory polarization of macrophages and inhibits reprogramming of macrophages into a pro‐resolution phenotype.Using 1D 1H Nuclear Magnetic Resonance (NMR) small molecule metabolomics in conjunction with immunologic profiling, we demonstrate substantial overlap between the metabolic profile of P. aeruginosa biofilm phenotype and the metabolic profile driving macrophage polarization either into the classical inflammatory phenotype (M1) or the non‐classical anti‐inflammatory phenotype (M2). This metabolic overlap included key metabolic pathways that regulate immunomodulation in macrophages such as shifts between the citrate cycle (TCA) and pentose phosphate metabolism (PPP) and selective amino acid metabolism. Furthermore, exposure of non‐polarized macrophages to medium conditioned with soluble, small molecule metabolites (&lt;3 kDa) derived either from P. aeruginosa planktonic cultures (referred to as PCM) or P. aeruginosa biofilm cultures (referred to as BCM) resulted in distinct metabolic profiles directly related to recently characterized metabolic pathways contributing to macrophage immunomodulation such as enhanced glycolysis, uncoupling of the TCA cycle, and selective amino acid uptake and metabolism. Finally, we use novel, naturally‐derived, biofilm‐targeted therapeutics to manipulate the biofilm immunomodulation of macrophage polarization to promote a shift from a pro‐inflammatory phenotype (M1) to a pro‐resolution phenotype (M2) in primary macrophages. Based on these findings, we demonstrate that P. aeruginosa biofilms mediate specific pathological effects against host macrophages through coordinated metabolic interactions, which result in chronic immune polarization and may contribute to deviation from the normal wound healing process and development of a chronic wound. Given the non‐invasive nature of NMR metabolomics profiling, these findings have the potential to lead to novel approaches for prevention and treatment of non‐healing wounds, including development of evidence‐based, personalizable treatment protocols executed at the bedside.Support or Funding InformationNIH NIGMS 1K01GM103821 to M.C.B.A. Kopriva Research Scholarship ‐ Montana State University to A.L.F.

Product Distribution Control for Glucosamine Condensation: Nuclear Magnetic Resonance (NMR) Investigation Substantiated by Density Functional Calculations

Selective conversion of glucosamine (GlcNH2) to deoxyfructosazine (DOF) and fructosazine (FZ) with additives was investigated. Significantly enhanced yield of DOF can be improved to 40.2% with B(OH)3 as the additive. Chemical shift titration (via one-dimensional nuclear magnetic resonance (1D 1H and 13C NMR)) and two-dimensional nuclear magnetic resonance (2D NMR) including 1H–13C HSQC and 1H–1H COSY are used to investigate intermolecular interactions between B(OH)3 and GlcNH2. Diffusion-ordered NMR spectroscopy (DOSY) was further employed to identify intermediate species. Mechanistic investigation by NMR combined with electron spray ionization–mass spectroscopy (ESI-MS) discloses that a mixed 1:1 boron complex was identified as the major species, shedding light on the promotional effects of B(OH)3, which is substantiated by density functional theory (DFT). Boron coordination effects make ring-opening and subsequent dehydration reaction thermodynamically and kinetically more favorable. Dehydration of dihy...

Nuclear Magnetic Resonance (NMR) Study for the Detection and Quantitation of Cholesterol in HSV529 Therapeutic Vaccine Candidate

This study describes the NMR-based method to determine the limit of quantitation (LOQ) and limit of detection (LOD) of cholesterol, a process-related impurity in the replication-deficient Herpes Simplex Virus (HSV) type 2 candidate vaccine HSV529. Three signature peaks from the 1D 1H NMR of a cholesterol reference spectrum were selected for the identification of cholesterol. The LOQ for a cholesterol working standard was found to be 1μg/mL, and the LOD was found to be 0.1μg/mL. The identity of cholesterol, separated from the formulation of growth supplement by thin layer chromatography (TLC), was confirmed by 1D 1H NMR and 2D 1H-13C HSQC NMR. The three signature peaks of cholesterol were detected only in a six-times concentrated sample of HSV529 candidate vaccine sample and not in the single dose HSV529 vaccine sample under similar experimental conditions. Taken together, the results demonstrated that NMR is a direct method that can successfully identify and quantify cholesterol in viral vaccine samples, such as HSV529, and as well as in the growth supplement used during the upstream stages of HSV529 manufacturing.

High-Throughput Indirect Quantitation of 13C Enriched Metabolites Using 1H NMR.

Nuclear magnetic resonance (NMR) spectroscopy is widely used in metabolomics to perform quantitative profiling of low-molecular weight compounds from biological specimens. The measurement of endogenous metabolites using NMR has proven to be a powerful tool to identify new metabolic biomarkers in physiological and pathological conditions, and to study and evaluate treatment efficiency. In this study we present a rapid approach to indirectly quantify 13C enriched molecules using one-dimensional (1D) 1H NMR. We demonstrate this approach using isotopically labeled [1,6-13C]glucose and in four different cell lines. We confirm the applicability of this approach for treatment follow-up, utilizing a renal cancer cell line with rapamycin as a tool compound to study changes in metabolic profiles. Finally, we validate the applicability of this method to study metabolic biomarkers from ex vivo tumor extracts, after infusion, using isotopically enriched glucose. Given the high throughput and increased sensitivity of direct-detect 1H NMR, this analytical approach provides an avenue for simple and rapid metabolic analysis of biological samples including blood, urine, and biopsies.

Automated Multicomponent Analysis of Soft Drinks Using 1D 1H and 2D 1H-1H J-resolved NMR Spectroscopy

Nuclear magnetic resonance (NMR) spectroscopy is evaluated as an efficient analytical technique for simultaneous identification and quantitation of multiple compounds in alcohol-free beverages. The method was validated for three different types of soft drinks, including a beverage with high sugar content, a diet product and an energy drink. The sample preparation required only 600 μL of degassed soft drink, 70 μL of 0.1 % TSP-d4 in D2O (for referencing and locking) and 100 μL of phosphate buffer (pH = 2.89). The simultaneous quantitative analysis of eleven compounds, such as sugars, flavourings, sweeteners, organic acids, alcohol (ethanol), vitamins and amino acids, was achieved using an automated procedure based on the PULCON principle (pulse length based concentration determination). Recovery rates were between 80 % (HMF) and 106 % (ethanol). The limits of quantitation (LOQ) varied between 52 mg/L for saccharin and 12 g/L for sucrose due to different matrix contents. Sample analysis time is about 25 min including sample preparation and automated data processing. A comparison with conventional methods showed the suitability of NMR for routine analysis of soft drinks.

Correction to On the Analytical Superiority of 1D NMR for Fingerprinting the Higher Order Structure of Protein Therapeutics Compared to Multidimensional NMR Methods

An important aspect in the analytical characterization of protein therapeutics is the comprehensive characterization of higher order structure (HOS). Nuclear magnetic resonance (NMR) is arguably the most sensitive method for fingerprinting HOS of a protein in solution. Traditionally, 1H–15N or 1H–13C correlation spectra are used as a “structural fingerprint” of HOS. Here, we demonstrate that protein fingerprint by line shape enhancement (PROFILE), a 1D 1H NMR spectroscopy fingerprinting approach, is superior to traditional two-dimensional methods using monoclonal antibody samples and a heavily glycosylated protein therapeutic (Epoetin Alfa). PROFILE generates a high resolution structural fingerprint of a therapeutic protein in a fraction of the time required for a 2D NMR experiment. The cross-correlation analysis of PROFILE spectra allows one to distinguish contributions from HOS vs protein heterogeneity, which is difficult to accomplish by 2D NMR. We demonstrate that the major analytical limitation of tw...

Metabolic profiling reveals anomalous energy metabolism and oxidative stress pathways in chronic fatigue syndrome patients

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating long-term multisystem disorder with a central and inexplicably persistent fatigue symptom that is unable to be relieved by rest. Energy metabolism and oxidative stress have been recent focal points of ME/CFS research and in this study we were able to elucidate metabolic pathways that were indicative of their dysfunction. Blood and urine samples were collected from 34 females with ME/CFS (34.9 ± 1.8 SE years old) and 25 non-ME/CFS female participants (33.0 ± 1.6 SE years old). All samples underwent metabolic profiling via 1D 1H Nuclear magnetic resonance spectroscopy and quantitated metabolites were assessed for significance. Blood glucose was elevated while blood lactate, urine pyruvate, and urine alanine were reduced indicating an inhibition of glycolysis that may potentially reduce the provision of adequate acetyl-CoA for the citric acid cycle. We propose that amino acids are being increasingly used to provide an adequate carbohydrate source for the citric acid cycle. We suggest that this is via glutamate forming 2-oxoglutarate through an enzyme that deaminates it and subsequently elevates blood aspartate. Dysfunctional energy metabolism appears to have impacted creatinine and its elevation in urine suggests that it may be used as an alternative for anaerobic ATP production within muscle. A decrease in blood hypoxanthine and an increase in urine allantoin further suggest the elevation of reactive oxygen species in ME/CFS patients. These findings bring new information to the research of energy metabolism, chronic immune activation and oxidative stress issues within ME/CFS.